Decision making is the process of selecting a possible course of action from all the available alternatives. In almost all such problems the multiplicity of criteria for judging the alternatives is pervasive. That is, for many such problems, the decision maker (OM) wants to attain more than one objective or goal in selecting the course of action while satisfying the constraints dictated by environment, processes, and resources. Another characteristic of these problems is that the objectives are apparently non- commensurable. Mathematically, these problems can be represented as: (1. 1 ) subject to: gi( ) 0, ', . . ., . ! where is an n dimensional decision variable vector. The problem consists of n decision variables, m constraints and k objectives. Any or all of the functions may be nonlinear. In literature this problem is often referred to as a vector maximum problem (VMP). Traditionally there are two approaches for solving the VMP. One of them is to optimize one of the objectives while appending the other objectives to a constraint set so that the optimal solution would satisfy these objectives at least up to a predetermined level. The problem is given as: Max f. ) 1 (1. 2) subject to: where at is any acceptable predetermined level for objective t. The other approach is to optimize a super-objective function created by multiplying each 2 objective function with a suitable weight and then by adding them together.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
EUR 7,22 expédition depuis Royaume-Uni vers France
Destinations, frais et délaisEUR 9,70 expédition depuis Allemagne vers France
Destinations, frais et délaisVendeur : Anybook.com, Lincoln, Royaume-Uni
Etat : Poor. Volume 164. This is an ex-library book and may have the usual library/used-book markings inside.This book has soft covers. In poor condition, suitable as a reading copy. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,750grams, ISBN:3540091114. N° de réf. du vendeur 7087993
Quantité disponible : 1 disponible(s)
Vendeur : Antiquariat Deinbacher, Murstetten, Autriche
8° , Softcover/Paperback. 1.Auflage,. XII, 351 Seiten Einband etwas berieben, Bibl.Ex., innen guter und sauberer Zustand 9783540091110 Sprache: Englisch Gewicht in Gramm: 588. N° de réf. du vendeur 154184
Quantité disponible : 1 disponible(s)
Vendeur : NEPO UG, Rüsselsheim am Main, Allemagne
Taschenbuch. Etat : Gut. 372 Seiten ex Library Book / aus einer wissenschafltichen Bibliothek / Sprache: Englisch. N° de réf. du vendeur 326677
Quantité disponible : 1 disponible(s)
Vendeur : NEPO UG, Rüsselsheim am Main, Allemagne
Etat : Gut. 372 Seiten ex Library Book / aus einer wissenschafltichen Bibliothek / Altersfreigabe FSK ab 0 Jahre Sprache: Englisch Gewicht in Gramm: 969 24,4 x 17,0 x 2,1 cm, Taschenbuch. N° de réf. du vendeur 366354
Quantité disponible : 1 disponible(s)
Vendeur : moluna, Greven, Allemagne
Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Decision making is the process of selecting a possible course of action from all the available alternatives. In almost all such problems the multiplicity of criteria for judging the alternatives is pervasive. That is, for many such problems, the decision ma. N° de réf. du vendeur 4880338
Quantité disponible : Plus de 20 disponibles
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - Decision making is the process of selecting a possible course of action from all the available alternatives. In almost all such problems the multiplicity of criteria for judging the alternatives is pervasive. That is, for many such problems, the decision maker (OM) wants to attain more than one objective or goal in selecting the course of action while satisfying the constraints dictated by environment, processes, and resources. Another characteristic of these problems is that the objectives are apparently non commensurable. Mathematically, these problems can be represented as: (1. 1 ) subject to: gi(~) ~ 0, ,', . . . , ! where ~ is an n dimensional decision variable vector. The problem consists of n decision variables, m constraints and k objectives. Any or all of the functions may be nonlinear. In literature this problem is often referred to as a vector maximum problem (VMP). Traditionally there are two approaches for solving the VMP. One of them is to optimize one of the objectives while appending the other objectives to a constraint set so that the optimal solution would satisfy these objectives at least up to a predetermined level. The problem is given as: Max f. ~) 1 (1. 2) subject to: where at is any acceptable predetermined level for objective t. The other approach is to optimize a super-objective function created by multiplying each 2 objective function with a suitable weight and then by adding them together. N° de réf. du vendeur 9783540091110
Quantité disponible : 1 disponible(s)
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Decision making is the process of selecting a possible course of action from all the available alternatives. In almost all such problems the multiplicity of criteria for judging the alternatives is pervasive. That is, for many such problems, the decision maker (OM) wants to attain more than one objective or goal in selecting the course of action while satisfying the constraints dictated by environment, processes, and resources. Another characteristic of these problems is that the objectives are apparently non commensurable. Mathematically, these problems can be represented as: (1. 1 ) subject to: gi(~) ~ 0, ,', . . . , ! where ~ is an n dimensional decision variable vector. The problem consists of n decision variables, m constraints and k objectives. Any or all of the functions may be nonlinear. In literature this problem is often referred to as a vector maximum problem (VMP). Traditionally there are two approaches for solving the VMP. One of them is to optimize one of the objectives while appending the other objectives to a constraint set so that the optimal solution would satisfy these objectives at least up to a predetermined level. The problem is given as: Max f. ~) 1 (1. 2) subject to: where at is any acceptable predetermined level for objective t. The other approach is to optimize a super-objective function created by multiplying each 2 objective function with a suitable weight and then by adding them together. 372 pp. Englisch. N° de réf. du vendeur 9783540091110
Quantité disponible : 2 disponible(s)
Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
Etat : New. In. N° de réf. du vendeur ria9783540091110_new
Quantité disponible : Plus de 20 disponibles
Vendeur : Chiron Media, Wallingford, Royaume-Uni
PF. Etat : New. N° de réf. du vendeur 6666-IUK-9783540091110
Quantité disponible : 10 disponible(s)
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
Taschenbuch. Etat : Neu. Neuware -Decision making is the process of selecting a possible course of action from all the available alternatives. In almost all such problems the multiplicity of criteria for judging the alternatives is pervasive. That is, for many such problems, the decision maker (OM) wants to attain more than one objective or goal in selecting the course of action while satisfying the constraints dictated by environment, processes, and resources. Another characteristic of these problems is that the objectives are apparently non commensurable. Mathematically, these problems can be represented as: (1. 1 ) subject to: gi(~) ~ 0, ,', . . . , ! where ~ is an n dimensional decision variable vector. The problem consists of n decision variables, m constraints and k objectives. Any or all of the functions may be nonlinear. In literature this problem is often referred to as a vector maximum problem (VMP). Traditionally there are two approaches for solving the VMP. One of them is to optimize one of the objectives while appending the other objectives to a constraint set so that the optimal solution would satisfy these objectives at least up to a predetermined level. The problem is given as: Max f. ~) 1 (1. 2) subject to: where at is any acceptable predetermined level for objective t. The other approach is to optimize a super-objective function created by multiplying each 2 objective function with a suitable weight and then by adding them together.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 372 pp. Englisch. N° de réf. du vendeur 9783540091110
Quantité disponible : 2 disponible(s)